Alignment is the work of making an AI do what people actually want, not just what they literally asked, and avoid what they would not want. Techniques include training on human feedback and writing rules the model is taught to follow.
It matters because a capable model that is slightly off target can cause harm at scale. You meet it in safety research, in model cards and in news about “misalignment”, when a model behaves in ways its makers did not intend.